Apply latent or observed models to fit data (e.g., SEM, CFA, mediation)
StatsFit(
latent = NULL,
latent.names = NULL,
observed = NULL,
observed.names = NULL,
additional = NULL,
additional.names = NULL,
DF,
params = NULL,
job.group = NULL,
initial.list = list(),
model.name,
jags.model,
custom.model = NULL,
run.ppp = FALSE,
run.robust = FALSE,
...
)latenr variables, Default: NULL
optional names for for latent variables, Default: NULL
observed variable(s), Default: NULL
optional names for for observed variable(s), Default: NULL
supplemental parameters for fitted data (e.g., indirect pathways and total effect), Default: NULL
optional names for supplemental parameters, Default: NULL
data to analyze
define parameters to observe, Default: NULL
for some hierarchical models with several layers of parameter names (e.g., latent and observed parameters), Default: NULL
initial values for analysis, Default: list()
name of model used
specify which module to use
define a custom model to use (e.g., string or text file (.txt), Default: NULL
logical, indicating whether or not to conduct ppp analysis, Default: FALSE
logical, indicating whether or not robust analysis, Default: FALSE
further arguments passed to or from other methods